Earticle

초록

영어

This study examines the performance of regime-based portfolio rebalancing strategies that utilize hidden Markov models (HMMs) to dynamically adjust asset allocations in response to volatility regime shifts. Based on a globally diversified portfolio reflecting the investment context of institutional investors with significant cross-border exposure, the analysis yields three key findings. First, regime-based strategies consistently outperform static strategic asset allocation (SAA) and buy-and-hold approaches in terms of risk-adjusted returns, while effectively reducing downside risk measures such as conditional value-at-risk (CVaR), maximum drawdown (MDD), and volatility. Second, the benefits of regime-based strategies are more pronounced at higher adjustment intensities, confirming their adaptability under shifting market conditions. Third, the performance advantages of regime-based strategies persist even after incorporating transaction costs. By integrating regime-based signals into the rebalancing process, this study provides empirical implications for institutional investors managing globally diversified portfolios in volatility-sensitive environments.

목차

Abstract
Ⅰ. Introduction
Ⅱ. Literature Review
Ⅲ. Empirical Findings
1. Descriptive Statistics and Correlation Analysis
2. Hidden Markov Model (HMM) for Volatility Regime Detection
3. Portfolio Characteristics Across Risk Adjustment Levels
4. Performance Comparison of Regime-Based and Benchmark Strategies
5. Performance Comparison: Regime-Based vs. Traditional Rebalancing Strategies
Ⅳ. Conclusion
References

키워드

저자

• Junho Hwang [ Deputy Research Fellow, National Pension Research Institute, National Pension Service ]
• Eunyoung Cho [ Assistant Professor, School of Business, Chungnam National University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  재무연구 [Asian Review of Financial Research]

• 간기

  계간

• pISSN

  1229-0351

• eISSN

  2713-6531

• 수록기간

  1988~2026

• 등재여부

  KCI 등재,SCOPUS

• 십진분류

  KDC 325 DDC 330